THE The Nexus Shift: From Insight to Impact (A Review)

Abstract

The emerging intricacies of organisational risks has challenged the association between the audit committee and governance structures. There is limited studies in terms of attributes and relational modalities of audit committee, limited research explored how AI transformed the governance association revolving the audit committee. This study explores this gap by reassessing the audit committee nexus in the age of artificial intelligence. Artificial Intelligence(AI) create an avenue to reshape audit committee from a retrospective oversight body into a prescient, intellectual driven governance structure. This conceptual framework postulates an AI-complemented Audit committee nexus that synthesise internal audit, enterprise risk management, continuous assurance, stakeholder communication and governance structures through AI-enabled technologies. Mingling the agency, resource, and stakeholders’ theories, the study embraced qualitative research approach, and review of literature. A conceptual approach was adopted, the study propounds a conceptual framework highlighting the connection between the audit committee characteristics, governance, audit assignments and firm’s result, and further describe how AI transform audit committee’s interaction with other governance mechanism. This study revealed that sound audit committee connection result in mitigation of fraud, enhanced transparency, corporate governance and long term economic development. The framework advances theoretical knowledge and practical direction by adding relevance to technology governance practices. AI-enabled assurance approaches and enhancement of auditor’s competency, and policy makers by adding knowledge to AI governance responsibilities and accountability mechanisms. It contributes to societal value by elongating assessment on responsible technology implementation and continuous governance Future research should assess the implementation, functionality, maturity and governance effect of AI-enabled audit committee models.